Zinc binding proteome of a phytopathogen Xanthomonas translucens pv. undulosa

Xanthomonas translucens pv. undulosa (Xtu) is a proteobacteria which causes bacterial leaf streak (BLS) or bacterial chaff disease in wheat and barley. The constant competition for zinc (Zn) metal nutrients contributes significantly in plant–pathogen interactions. In this study, we have employed a systematic in silico approach to study the Zn-binding proteins of Xtu. From the whole proteome of Xtu, we have identified approximately 7.9% of proteins having Zn-binding sequence and structural motifs. Further, 115 proteins were found homologous to plant–pathogen interaction database. Among these 115 proteins, 11 were predicted as putative secretory proteins. The functional diversity in Zn-binding proteins was revealed by functional domain, gene ontology and subcellular localization analysis. The roles of Zn-binding proteins were found to be varied in the range from metabolism, proteolysis, protein biosynthesis, transport, cell signalling, protein folding, transcription regulation, DNA repair, response to oxidative stress, RNA processing, antimicrobial resistance, DNA replication and DNA integration. This study provides preliminary information on putative Zn-binding proteins of Xtu which may further help in designing new metal-based antimicrobial agents for controlling BLS and bacterial chaff infections on staple crops.

Metal-PDB and arises from the exceptionally long distance cutoff used to define Zn-sites. The reference used to support this cutoff is quite dated (from 1990) and a more stringent cutoff is recommended to at least define the primary coordination environment. A second range of distances could be used to capture residues more commonly found in 2nd and 3rd sphere coordination environments. Articles by Dudev and Lim provide detailed coverage of metal site geometries in proteins and could be used to guide the establishment of these boundaries. A second issue is whether all of these Zn-sites in the Metal PDB are actually Zn-loaded proteins in the cell, or are merely Zn-substituted proteins and the motif to which they bind is not evolved to bind Zn in the cell, thus losing its predictive value and creating false positives (see also later comments regarding Table S2).
Similarly, there is annotation of proteins as Zn-binding in various databases (section 3.2) which may result from data with purified proteins to which Zn will bind more tightly than metals such as Fe, which could be the physiological cofactor. Again, some false positives might emerge in the analysis. The latter section looking for possible secreted Zn-proteins that could be involved in hostpathogen interaction is of interest but there is no critical consideration of whether these proteins are secreted under conditions linked to host-interactions. Figure 7 is hard to understand. The Zn-coordination environments depicted here are incomplete, often showing two protein ligands when the expected minimal coordination would be three protein ligands. Additionally, it is not clear that the structures represent what the panel claims. For example, 7e is labelled as the ClpX four Cys Zn-finger but a four Cys Zn-finger is not represented.
Other comments:  Table 2 is very hard to navigate and thus use effectively. The binding site column shows too few residues in some cases (the first entry) and the Zn-ligand distances (final column) are sometimes not listed, are too long to be primary coordination interactions, or include an indication that the ligand is not one given in the binding site column. As indicated above in the comment for Figure 1, a rigorous cutoff defined by verified Zn-binding sites should be employed here. Also, as mentioned above, this table has captured Zn-substituted proteins that use a different metal for biological activity (eg, entry 270 cites PDBID 1irn, which is a Zn-substituted rubredoxin, normally an Fe protein).
The predicted protein structures using Phyre2 should be made available to allows others to assess the nature of the Zn site to enable study of these proteins (eg to generate site-directed mutants).

09-Jul-2019
Dear Dr Verma, The editors assigned to your paper ("Zinc binding proteome of a phytopathogen Xanthomonas translucens pv. undulosa") have now received comments from reviewers.
Both reviewers raise a very significant number criticisms and concerns with the work and analysis as currently presented. These will all require very careful consideration. We would therefore like you to revise your paper in accordance with the referee's points which can be found below (not including confidential reports to the Editor). Please note this decision does not guarantee eventual acceptance.
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We suggest the following format: AB carried out the molecular lab work, participated in data analysis, carried out sequence alignments, participated in the design of the study and drafted the manuscript; CD carried out the statistical analyses; EF collected field data; GH conceived of the study, designed the study, coordinated the study and helped draft the manuscript. All authors gave final approval for publication.
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Once again, thank you for submitting your manuscript to Royal Society Open Science and I look forward to receiving your revision. If you have any questions at all, please do not hesitate to get in touch. Comments to the Author(s) The manuscript focuses on a broadly important issue, the proteome of a bacterial plant pathogen. The importance of enumerating the metalloproteins of these organisms is well-described in the introduction. The authors focus on Zn-proteins to "understand the Zn homeostatic mechanism" (p. 3 line 59-60). They argue for non-experimental pipelines to rapidly identify metalloproteins and have presented such a work-flow here. Ultimately the mechanism of Zn-homeostasis (eg, balancing Zn supply with demand), which is well-studied in several bacteria (E. coli, B. subtilis, Staphylococcus) is not really addressed.
The work-flow has a logic to it, but a number of questions arise from the analysis that result from a loose definition of Zn sites. Critically, the value of the information provided is limited by the potential for false positives. Additionally, it is not clear whether this approach has identified novel Zn-proteins from Xanthomonas that would be interesting targets for inhibitor design because of the potential for high selectivity.
First, the authors rely on Metal PDB to define minimal functional Zn sites (p4. Line 30-31.) in the proteins from their organism. However, the outcome of this analysis (presented in part in Figure  1) shows a moderate abundance of Arg residues in Zn-binding sites. This is at odds with the Metal-PDB and arises from the exceptionally long distance cutoff used to define Zn-sites. The reference used to support this cutoff is quite dated (from 1990) and a more stringent cutoff is recommended to at least define the primary coordination environment. A second range of distances could be used to capture residues more commonly found in 2nd and 3rd sphere coordination environments. Articles by Dudev and Lim provide detailed coverage of metal site geometries in proteins and could be used to guide the establishment of these boundaries. A second issue is whether all of these Zn-sites in the Metal PDB are actually Zn-loaded proteins in the cell, or are merely Zn-substituted proteins and the motif to which they bind is not evolved to bind Zn in the cell, thus losing its predictive value and creating false positives (see also later comments regarding Table S2).
Similarly, there is annotation of proteins as Zn-binding in various databases (section 3.2) which may result from data with purified proteins to which Zn will bind more tightly than metals such as Fe, which could be the physiological cofactor. Again, some false positives might emerge in the analysis. The latter section looking for possible secreted Zn-proteins that could be involved in hostpathogen interaction is of interest but there is no critical consideration of whether these proteins are secreted under conditions linked to host-interactions. Figure 7 is hard to understand. The Zn-coordination environments depicted here are incomplete, often showing two protein ligands when the expected minimal coordination would be three protein ligands. Additionally, it is not clear that the structures represent what the panel claims. For example, 7e is labelled as the ClpX four Cys Zn-finger but a four Cys Zn-finger is not represented.
Other comments:  Table 2 is very hard to navigate and thus use effectively. The binding site column shows too few residues in some cases (the first entry) and the Zn-ligand distances (final column) are sometimes not listed, are too long to be primary coordination interactions, or include an indication that the ligand is not one given in the binding site column. As indicated above in the comment for Figure 1, a rigorous cutoff defined by verified Zn-binding sites should be employed here. Also, as mentioned above, this table has captured Zn-substituted proteins that use a different metal for biological activity (eg, entry 270 cites PDBID 1irn, which is a Zn-substituted rubredoxin, normally an Fe protein).
The predicted protein structures using Phyre2 should be made available to allows others to assess the nature of the Zn site to enable study of these proteins (eg to generate site-directed mutants).

Editorial Office Comments to Author:
For information about language editing services endorsed by the Royal Society, please follow the link below: https://royalsociety.org/journals/authors/language-polishing/ Author's Response to Decision Letter for (RSOS-190369

RSOS-190369.R1 (Revision)
Review form: Reviewer 2 Is the manuscript scientifically sound in its present form? Yes

Do you have any ethical concerns with this paper? No
Have you any concerns about statistical analyses in this paper? No

Recommendation?
Accept as is

Comments to the Author(s)
The revised manuscript address concerns raised in review. The authors have done a nice job with the revision. The inclusion of the Phyre predicted structures (in the .rar file) means that a reader can see the predicted site in combination with information in the Tables within the paper. This is particularly important for a researcher who, for instance, carries out a genetic screen and fits a hit in a gene that encodes a putative Zn-protein or enzyme. This study would enable that individual to make site-directed mutation to test the role of Zn in function.

21-Aug-2019
Dear Dr Verma, I am pleased to inform you that your manuscript entitled "Zinc binding proteome of a phytopathogen Xanthomonas translucens pv. undulosa" is now accepted for publication in Royal Society Open Science.
You can expect to receive a proof of your article in the near future. Please contact the editorial office (openscience_proofs@royalsociety.org and openscience@royalsociety.org) to let us know if you are likely to be away from e-mail contact --if you are going to be away, please nominate a coauthor (if available) to manage the proofing process, and ensure they are copied into your email to the journal.
Due to rapid publication and an extremely tight schedule, if comments are not received, your paper may experience a delay in publication.
Royal Society Open Science operates under a continuous publication model (http://bit.ly/cpFAQ). Your article will be published straight into the next open issue and this will be the final version of the paper. As such, it can be cited immediately by other researchers. As the issue version of your paper will be the only version to be published I would advise you to check your proofs thoroughly as changes cannot be made once the paper is published. Comments to the Author(s) The revised manuscript address concerns raised in review. The authors have done a nice job with the revision. The inclusion of the Phyre predicted structures (in the .rar file) means that a reader can see the predicted site in combination with information in the Tables within the paper. This is particularly important for a researcher who, for instance, carries out a genetic screen and fits a hit in a gene that encodes a putative Zn-protein or enzyme. This study would enable that individual to make site-directed mutation to test the role of Zn in function.

Review of Zinc-binding Proteome of a Phytopathogen Xanthomonas…
The authors present an in silico bioinformatics analysis of the genome of Xanthomonas translucens pv. Undulosa directed at uncovering potential Zn-binding proteins in the proteome and describing their functionality, particularly in relation to pathogenicity. The reviewer is an experimentalist working in the area of Zn-proteomics and Zn-trafficking. Thus, I will not directly assess the adequacy of the bioinformatics methods applied in this study. I will address other aspects of the manuscript.
First, the manuscript needs thorough editing to reach the standard of grammatical and idiomatic English (e.g. Page 1, line 50; Page 2, lines 18-23 and many more).
Second, I am sympathetic to this type of bioinformatics analysis which leads to the definition of a hypothetical Zn-proteome for this organism. But I am concerned that it is missing a lot of information that will allow the reader to assess the meaning and quality of the results. Therefore, I will move through the manuscript sequentially to raise concerns that the authors need to address.
Page 2, line 2 -2:2 "This study provides primarily information to understand the Zn homeostatic mechanism of Xtu." 2:60 "To understand the Zn homeostatic mechanism of a bacterial pathogen the key requirement is to accomplish inclusive facts of the Zn-binding proteins of that pathogen [19]." 3:17-18 "This primarily study helps in understanding the Zn homeostatic mechanism of Xtu which further may aids in controlling BLS." Will the results provide insight into Zn homeostatic mechanisms? I do not think so. Zn homeostasis maintains the correct Zn-proteome in the face of changing circumstances for the cell. But knowledge of the total Zn-proteomethe subject of this manuscript (3:11-13) -will not lead to an understanding of Zn homeostasis. So these statements need to be removed.  (Table S4) are connected to one another because the writing is so tiny. These figures need to be revised.

5:30-31
"In order to check the regulation of biological process by Zn binding Proteins, the analysis of the network was made and number of interactions was estimated." Define regulation and then explain how GO networks relate to regulation by Zn binding proteins. I would say that the GO networks show the 'involvement' of Zn binding proteins in metabolic processes not the 'regulation'.

6:4
The Discussion seeks to relate the bioinformatics results with experimental results, showing that at least some of the proteins identified have already been shown to be Zn-proteins. That is important. Some of the references supporting the text that follows clearly relate members of the list of putative Zn-proteins to such experimental results. But a sampling of other references was unconvincing in providing this support. I will mention these as they appear in the manuscript.

6:6
"The present study focuses on the screening of Zn-binding proteins from the whole proteome of Xtu." Please substitute, "The present study focuses on the bioinformatic identification of potential Zn-proteins" within the whole proteome of Xtu Comment 3: Page 2, line 2 -2:2 "This study provides primarily information to understand the Zn homeostatic mechanism of Xtu." 2:60 "To understand the Zn homeostatic mechanism of a bacterial pathogen the key requirement is to accomplish inclusive facts of the Zn-binding proteins of that pathogen [19]." 3:17-18 "This primarily study helps in understanding the Zn homeostatic mechanism of Xtu which further may aids in controlling BLS." Will the results provide insight into Zn homeostatic mechanisms? I do not think so. Zn homeostasis maintains the correct Zn-proteome in the face of changing circumstances for the cell. But knowledge of the total Zn-proteomethe subject of this manuscript (3:11-13) -will not lead to an understanding of Zn homeostasis. So these statements need to be removed. Our response 3: We have removed these statements from the revised manuscript.  which were already known and specified in Protein Data Bank. We have prepared local dataset of these known Zn-binding proteins and performed BlastP search of Xtu proteome with this database. The proteins which showed homology with this local database at evalue less than equal to 0.00001 were listed as putative Zn-binding proteins having Znbinding sequence motifs. Further to determine structural Zn-binding sites in the shortlisted proteins we have used Metal ion binding prediction and docking server (MIB). This server takes input file in PDB format, so we have first modeled the 3D-structures of the shortlisted proteins by Phyre2 server and then performed MIB search. MIB server is based on a fragment transformation method. In this method the query protein was aligned to the metal binding templates those were extracted from metal bound proteins present in PDB. The templates represent the local structure of metal binding residues within 3.5Å. According to MIB server a metal binding site had to contain a metal ion and at least two residues to quantify as a metal ion binding residue template. Each cluster after sequence and structural similarity acquire a score which is used for prediction of metal binding sites. For the evaluation of sequence similarity, MIB server utilizes BLOSUMM62 matrix and for calculation of structural similarity root mean square deviation of Cα atoms of the alignments was used. At more than 95% specificity threshold, MIB server predicts the Znbinding proteins with 94.8% accuracy and 71.1% sensitivity. To check the interactions of MIB docked metal ion with the protein we have used Ligplot + visualization tool. We found that interacting residues and interaction radii provided by MIB may vary in wide range. Therefore, the interaction distance was raised from primary sphere (up to 3.5Å) (provided by MIB server) to secondary sphere (5Å). As it was stated earlier that second shell of interactions helps in stabilizing metal binding site, raise metal affinity and play role in determining physical properties of transition metal complexes (Shook and Borovik, 2010;Ngo et al., 2015;Dudev and Lim 2013). determinants of metal ion selectivity in proteins. Chemical reviews, 114(1), 538-556. Earlier it was stated that in a cell the cytosolic Zn-binding proteins, transporters localized in cytoplasmic membranes and sensors of cytoplasmic free Zn ions are the molecules involved in Zn-homeostatic mechanisms (Colvin et al., 2010). In our study we have provided the primarily information of Zn-proteome of Xtu.  Colvin RA, Holmes WR, Fontaine CP, Maret W. 2010 Cytosolic zinc buffering and muffling: Their role in intracellular zinc homeostasis. Metallomics 2, 306-317. We have used MetalPDB and MIB servers which rely on PDB database as a source and contain not only Zn-binding proteins but also have Zn-substituted proteins and proteins participate as part of Zn buffering system. In PDB database biological assemblies of some proteins are available and some of the proteins are present as asymmetric unit, shows only one or two residues binding to the metal atom. In biological active form many of the proteins exists as more than one copy (dimer, trimer, tetramer and hexamer) and metal at their interface. Further, in some cases ligand atom of the protein may bind to metal ion for their stable coordination in biological active form. Therefore, our in-silico prediction we have not determined the coordination geometry of the proteins, but we have found the proteins having Zn-binding motifs and found their probable binding site based on fragment transformation method. In the revised manuscript we have now provided this information. Comment 9: 4:53 What is meant by "the order of interactions"? From Figure 1 it seems that the intent is simply to show quantitatively how often different ligands are used in putative Znbinding sites. Our response 9: We have now corrected the statement in revised manuscript.  (Table S4) are connected to one another because the writing is so tiny. These figures need to be revised. Our response: The Gene ontology represents the common classification scheme for gene function. The GO network was constructed based on the GO of the predicted Zn-binding proteins using ClueGO plug in cytoscape. Regarding the size of GO terms level in the figures we are unable to raise their size as this figure is generated by cytoscape. Although, we have now improved the Table S4. In these tables the GO terms that belong to same groups are connected to each other. The GO term present in multiple groups are also connected to other groups which indicate their probable role in multiple processes. Grouping is based on Kappa score. Further we have also provided the list of GO term associated genes which belong to predicted Zn-binding proteins in supplementary tables (4 and 5). The connections between the GO terms and genes were not shown in the networks (figures) as it is hard to show all the connections provided in these complex networks.
Comment 11: 5:30-31 "In order to check the regulation of biological process by Zn binding Proteins, the analysis of the network was made and number of interactions was estimated." Define regulation and then explain how GO networks relate to regulation by Zn binding proteins. I would say that the GO networks show the 'involvement' of Zn binding proteins in metabolic processes not the 'regulation'. Our response 11: Yes, we are agreed with the reviewer comment. We have now replaced the word regulation with involvement. Please see: Page no. 6 line no.22-23.
Comment 12: 6:4 The Discussion seeks to relate the bioinformatics results with experimental results, showing that at least some of the proteins identified have already been shown to be Znproteins. That is important. Some of the references supporting the text that follows clearly relate members of the list of putative Zn-proteins to such experimental results. But a sampling of other references was unconvincing in providing this support. I will mention these as they appear in the manuscript. Our response 12: We are thankful to the reviewer for reviewing our manuscript critically and providing valuable suggestions. We have put our full efforts to improve the manuscript.
Comment 13: 6:6 "The present study focuses on the screening of Zn-binding proteins from the whole proteome of Xtu." Please substitute, "The present study focuses on the bioinformatic identification of potential Zn-proteins" within the whole proteome of Xtu Our response 13: We have changed the statement in the revised manuscript. This study provides an in-silico report on Zn-binding proteins of Xtu. For the prediction of Zn-binding proteins and their functional annotation we rely on bioinformatics servers and the supported literature. The predicted proteins are putative and need further experimental validation. Regarding the metal binding site and stability of the proteins we have explained earlier in above comment that computational databases and tools not only rely on biological assemblies but also on asymmetric unit. Further, regarding the workflow of the study we have not only predicted the Zn-binding proteins but also annotated these based on their domains and GO. Also, we have provided the supported literature which indicate that these predicted proteins probably have affinity for Zn.

Point by point response to the Reviewer 2 comments
Comment 1: Comments to the Author(s) The manuscript focuses on a broadly important issue, the proteome of a bacterial plant pathogen. The importance of enumerating the metalloproteins of these organisms is well-described in the introduction. The authors focus on Zn-proteins to "understand the Zn homeostatic mechanism" (p. 3 line 59-60). They argue for non-experimental pipelines to rapidly identify metalloproteins and have presented such a work-flow here. Ultimately the mechanism of Zn-homeostasis (eg, balancing Zn supply with demand), which is well-studied in several bacteria (E. coli, B. subtilis, Staphylococcus) is not really addressed. Our response1: We are highly thankful to the reviewer for reviewing our manuscript critically.
We have now addressed the Zn homeostasis mechanism of some bacteria. Please see Page no. 3 line no. 1-16.

Comment 2:
The work-flow has a logic to it, but a number of questions arise from the analysis that result from a loose definition of Zn sites. Critically, the value of the information provided is limited by the potential for false positives. Additionally, it is not clear whether this approach has identified novel Zn-proteins from Xanthomonas that would be interesting targets for inhibitor design because of the potential for high selectivity. First, the authors rely on Metal PDB to define minimal functional Zn sites (p4. Line 30-31.) in the proteins from their organism. However, the outcome of this analysis (presented in part in Figure 1) shows a moderate abundance of Arg residues in Zn-binding sites. This is at odds with the Metal-PDB and arises from the exceptionally long distance cutoff used to define Zn-sites. The reference used to support this cutoff is quite dated (from 1990) and a more stringent cutoff is recommended to at least define the primary coordination environment. A second range of distances could be used to capture residues more commonly found in 2nd and 3rd sphere coordination environments. Articles by Dudev and Lim provide detailed coverage of metal site geometries in proteins and could be used to guide the establishment of these boundaries. A second issue is whether all of these Zn-sites in the Metal PDB are actually Zn-loaded proteins in the cell, or are merely Zn-substituted proteins and the motif to which they bind is not evolved to bind Zn in the cell, thus losing its predictive value and creating false positives (see also later comments regarding Table S2). Our response 2: We are highly thankful to the reviewer for reviewing our manuscript. We have used MetalPDB database for the collection of Zn-binding proteins which were already known and specified in Protein Data Bank. We have prepared local dataset of these known Zn-binding proteins and performed BlastP search of Xtu proteome with this database. The proteins which showed homology with this local database at e-value less than equal to 0.00001 were listed as putative Zn-binding proteins having Zn-binding sequence motifs. Further to determine structural Zn-binding sites in the shortlisted proteins we have used Metal ion binding prediction and docking server (MIB). This server takes input file in PDB format so we have first modeled the 3D-structures of the shortlisted proteins by Phyre2 server and then performed MIB search. MIB server based on a fragment transformation method. In this method the query protein was aligned to the metal binding templates those were extracted from metal bound proteins present in PDB. The templates represent the local structure of metal binding residues within 3.5Å. According to MIB server a metal binding site had to contain a metal ion and at least two residues to quantify as a metal ion binding residue template. Each cluster after sequence and structural similarity acquire a particular score which is used for prediction of metal binding sites. For the evaluation of sequence similarity, MIB server utilizes BLOSUMM62 matrix and for calculation of structural similarity root mean square deviation of Cα atoms of the alignments was used. At more than 95% specificity threshold, MIB server predicts the Zn-binding proteins with 94.8% accuracy and 71.1% sensitivity.To check the interactions of MIB docked metal ion with the protein we have used Ligplot + visualization tool. We found that interacting residues and interaction radii provided by MIB may vary in wide range. Therefore, the interaction distance was raised from primary sphere (up to 3.5Å) (provided by MIB server) to secondary sphere (5Å). As it was stated earlier that second shell of interactions helps in stabilizing metal binding site, raise metal affinity and play role in determining physical properties of transition metal complexes (Shook and Borovik, 2010;Ngo et al., 2015;Dudev and Lim 2013). Yes, MetalPDB database contain all Zn-binding sites i.e all Zn-loaded proteins in the cell or Znsubstituted proteins. Further, the logic behind their consideration is that the Zn substituted proteins may have potential to bind Zn ion also. Therefore, it may act as putative target to inhibit the activity of that protein or for designing metal-based inhibitors. Comment 3: Similarly, there is annotation of proteins as Zn-binding in various databases (section 3.2) which may result from data with purified proteins to which Zn will bind more tightly than metals such as Fe, which could be the physiological cofactor. Again, some false positives might emerge in the analysis. Our response 3: As we mentioned in the above response that MetalPDB contained all Znbinding proteins including Zn substituted proteins. So, our prediction also includes putative Zn substituted proteins. Further, the logic behind their consideration is that the Zn substituted proteins may have potential to bind Zn ion also. Therefore, it may act as putative target to inhibit the activity of that particular protein or for designing metalbased inhibitors.
Comment 4: The latter section looking for possible secreted Zn-proteins that could be involved in host-pathogen interaction is of interest but there is no critical consideration of whether these proteins are secreted under conditions linked to host-interactions. Our response 4: In this in silico study we have first checked that putative Zn binding proteins showed similarity with Pathogen Host interaction database (PHI-dataase). PHI-database contains experimentally validated virulent and effector proteins which were known to play role in pathogen-host interactions. We have shortlisted the proteins which were homologous to PHI-database and considered that these may involve in plant-pathogen interactions. Further, from these we have extracted the secreted proteins. So, we have putatively considered that these secreted Zn-binding proteins probably involved in pathogen-host interactions.
Comment 5: Figure 7 is hard to understand. The Zn-coordination environments depicted here are incomplete, often showing two protein ligands when the expected minimal coordination would be three protein ligands. Additionally, it is not clear that the structures represent what the panel claims. For example, 7e is labelled as the ClpX four Cys Zn-finger but a four Cys Zn-finger is not represented. Our response 5: In this study we have tried to find the proteins whether the protein is Znbinding or not i.e proteins have ability to bind Zn 2+ or not. For this prediction we rely on MetalPDB database and MIB server. As stated, above MetalPDB database contain all Znbinding proteins including Zn-substituted proteins. And secondly, we have used MIB server which is based on fragment transformation method and uses a template for prediction having a metal ion and at least two interacting residues within 3.5Ȧ. Further, both the server does not only rely on biological assemblies of the proteins as uses PDB database as a source. In biological active form many of the proteins exists as more than one copy (dimer, trimer, tetramer and hexamer) and metal at their interface. In PDB database some proteins are present as asymmetric unit shows only one or two residues binding to the metal atom. Further, in some cases ligand atom may bind to metal ion for their stable coordination in biological active form. Therefore, our in-silico prediction we have not determined the coordination geometry of the proteins, but we have found the proteins having Zn-binding motifs and found their probable binding site based on fragment transformation method. In figure 7, we have simply showed some representative structures of the putative Zn-binding proteins. Yes, we agreed with the reviewer that this figure do not contribute much in our study, so we have removed this figure in the revised manuscript. Secondly, figure 7e represents the interacting residues predicted by MIB server which is based on fragment transformation method. Further, when we analyzed the given protein for its domain using InterProScan and Pfam databases we found that it contains ClpX domain. This may be because MIB used fragment transformation method for prediction of binding site and docking and at more than 95% specificity threshold, MIB server predicts the Zn-binding sites with 94.8% accuracy and 71.1% sensitivity.
Other comments:  2+ . Various studies are made on Znsubstituted cytochrome P450. As we mentioned in the above response that MetalPDB contained all Zn-binding proteins including Zn substituted proteins and hence our study also has all these proteins. Further, a study indicates that Zn 2+ ion have inhibitory effect on human cytochrome P450 3A4 activity.